title: Exponential passivity of memristive neural networks with time delays.
abstract: Memristive neural networks are studied across many fields of science. To uncover their structural design principles, the paper introduces a general class of memristive neural networks with time delays. Passivity analysis is conducted by constructing suitable Lyapunov functional. The analysis in the paper employs the results from the theories of nonsmooth analysis and linear matrix inequalities. A numerical example is provided to illustrate the effectiveness and less conservatism of the proposed results.
authors.affiliation: College of Mathematics and Statistics, Hubei Normal University, Huangshi 435002, China; Institute for Information and System Science, Xi'an Jiaotong University, Xi'an 710049, China; School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: alequ@126.com.
authors.forename: Ailong
authors.initials: A
authors.lastname: Wu
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Zeng
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003203:Computers, Hybrid; D016014:Linear Models; D008568:Memory; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors
keywords: Exponential passivity; Hybrid systems; Memristive neural networks